TY - JOUR

T1 - On communication protocols that compute almost privately

AU - Comi, Marco

AU - Dasgupta, Bhaskar

AU - Schapira, Michael

AU - Srinivasan, Venkatakumar

PY - 2012/10/26

Y1 - 2012/10/26

N2 - We further investigate and generalize the approximate privacy model recently introduced by Feigenbaum et al. (2010) [7]. We explore the privacy properties of a natural class of communication protocols that we refer to as "dissection protocols". Informally, in a dissection protocol the communicating parties are restricted to answering questions of the form "Is your input between the values α and β (under a pre-defined order over the possible inputs)?". We prove that for a large class of functions, called tiling functions, there always exists a dissection protocol that provides a constant average-case privacy approximation ratio for uniform or "almost uniform" probability distributions over inputs. To establish this result we present an interesting connection between the approximate privacy framework and basic concepts in computational geometry. We show that such a good privacy approximation ratio for tiling functions does not, in general, exist in the worst case. We also discuss extensions of the basic setup to more than two parties and to non-tiling functions, and provide calculations of privacy approximation ratios for two functions of interest.

AB - We further investigate and generalize the approximate privacy model recently introduced by Feigenbaum et al. (2010) [7]. We explore the privacy properties of a natural class of communication protocols that we refer to as "dissection protocols". Informally, in a dissection protocol the communicating parties are restricted to answering questions of the form "Is your input between the values α and β (under a pre-defined order over the possible inputs)?". We prove that for a large class of functions, called tiling functions, there always exists a dissection protocol that provides a constant average-case privacy approximation ratio for uniform or "almost uniform" probability distributions over inputs. To establish this result we present an interesting connection between the approximate privacy framework and basic concepts in computational geometry. We show that such a good privacy approximation ratio for tiling functions does not, in general, exist in the worst case. We also discuss extensions of the basic setup to more than two parties and to non-tiling functions, and provide calculations of privacy approximation ratios for two functions of interest.

KW - Approximate privacy

KW - Binary space partition

KW - Multi-party communication

KW - Tiling

UR - http://www.scopus.com/inward/record.url?scp=84865500745&partnerID=8YFLogxK

U2 - 10.1016/j.tcs.2012.07.008

DO - 10.1016/j.tcs.2012.07.008

M3 - Article

AN - SCOPUS:84865500745

SN - 0304-3975

VL - 457

SP - 45

EP - 58

JO - Theoretical Computer Science

JF - Theoretical Computer Science

ER -